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    Pawel Jakubas

    Machine Learning/Data science/Functional programming

    With a diverse educational background encompassing Energy Engineering, Banking, Finance, Physics, and Mechatronics, Pawel Jakubas is a seasoned professional with a unique blend of expertise in both business and technology.

    His skill set includes predictive analytics, data science, machine learning, distributed computing, and software architecture. Pawel excels in designing and implementing complex software solutions through a functional approach.

    Pawel's current technology stack spans a range of languages such as Haskell, Elm, R, and Python. He is well-versed in industrial ML/DS methodologies like CRISP-DM, as well as deep learning frameworks like TensorFlow and Keras. Additionally, he has experience in probabilistic programming.

    His proficiency extends to big data and distributed systems including technologies like Druid, Kafka, Spark, Flink, and Hadoop zoo. Pawel is also skilled in private cloud environments, AWS, ansible, and docker.

    Having a PhD in Physics, an MSc in Mechatronics, and an MSc in Finance and Banking, Pawel has a rich academic background. He has worked in academia focusing on condensed matter theory, as well as in leading technology companies such as Samsung Electronics and two high-tech startups.

    Throughout his career, Pawel has held various roles including Haskell Developer at Input Output HK, Machine Learning Technologist, Data Scientist, and Functional Programmer at Aiccurate, Chief Technology Officer, Big Data Expert, Data Science Specialist, AI Professional, and Full-Stack Programmer at Deep.Bi, Software Engineer at Samsung Electronics, and Researcher at the Institute of Physics, Polish Academy of Sciences.

    Pawel Jakubas
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    Location

    Warsaw, Masovian District, Poland